The meat industry is becoming increasingly automated with the goal of becoming more efficient. Automated accurate measurement of the properties of animal tissue is therefore important to ensure efficient operation.
In particular, the accurate measurement of the composition and structure of meat carcasses, including fat depth, bone location and muscle thickness, is typically required. The measurement process is preferably non-contact to allow easier and faster measurement and assist in avoiding problems with contamination and cleaning.
Electromagnetic sensors, in particular microwave sensors have been used to detect the properties of animal tissue. Typical problems associated with the use of microwave energy include the need to focus the energy into a relatively small area or voxel, accounting for the different permittivity between different tissue samples, inaccuracies due to surface variation and the requirement for a robust sensor.
Known methods for focussing electromagnetic radiation into a voxel include the use of lenses, reflectors and synthetic aperture methods. These focus the radiation onto a specific area of the tissue and a measurement is taken of the reflected or scattered radiation. Different materials within the tissue are then detected by the energy of the reflected waves.
Traditionally, wide band signals have been used for the detection of the properties of tissue in order to obtain a required resolution. These may then be analysed using Fourier Transform and spectral estimation techniques. A disadvantage of using wide band signals is the generation of numerous spurious reflections and the requirement to use more complex and costly equipment capable of generating a wide range of frequencies. Also, the swept frequency range can not be reduced without sacrificing resolution in the detected signals. Furthermore, the generation and detection of a wide band signal requires relatively expensive equipment in comparison to narrow band systems. Problems are also encountered when attempting to measure the thickness of fat tissue as it is necessary to resolve the position of the small reflection that arises from the air-fat interface from the much larger and swamping reflection from the fat-meat interface.
The widely used Fast Fourier Transform Technique, when used over a limited bandwidth gives rise to significant errors for relatively minor errors in phase if unknown incidental scatterers are unaccounted for. Therefore, the position and response of these incidental scatterers must be determined for accurate measurement. This is acceptable only if long multiple path scatter is ignored. Spectral estimation techniques are a known method of accounting for the incidental scatterers. However, the computational burden of spectral estimation techniques is relatively expensive, requiring relatively high performance processors and therefore is not well suited to a harsh environment, due to lack of robustness.